Systems and Methods for IQ Detection

ABSTRACT

A system and method for combining multiple functions of a light detection and ranging (LIDAR) system includes receiving a second optical beam generated by the laser source or a second laser source, wherein the second optical beam is associated with a second local oscillator (LO); splitting the second optical beam into a third split optical beam and a fourth split optical beam; transmitting, to the optical device, the third split optical beam and the fourth split optical beam; receiving, from the optical device, a third reflected beam that is associated with the third split optical beam and a fourth reflected beam that is associated with the fourth split optical beam; and pairing the third reflected beam with the second LO signal and the fourth reflected beam with the second LO signal.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a Continuation of U.S. patent applicationSer. No. 16/915,404, filed Jun. 29, 2020. The entire disclosure of U.S.patent application Ser. No. 16/915,404 is incorporated herein byreference.

BACKGROUND

Optical detection of range using lasers, often referenced by a mnemonic,LIDAR, for light detection and ranging, also sometimes called laserRADAR, is used for a variety of applications, from altimetry, toimaging, to collision avoidance. LIDAR provides finer scale rangeresolution with smaller beam sizes than conventional microwave rangingsystems, such as radio-wave detection and ranging (RADAR). Opticaldetection of range can be accomplished with several differenttechniques, including direct ranging based on round trip travel time ofan optical pulse to an object, and chirped detection based on afrequency difference between a transmitted chirped optical signal and areturned signal scattered from an object, and phase-encoded detectionbased on a sequence of single frequency phase changes that aredistinguishable from natural signals.

SUMMARY

Aspects of the present disclosure relate generally to light detectionand ranging (LIDAR) in the field of optics, and more particularly tosystems and methods for combining multiple functions of a LIDAR system,to support the operation of a vehicle.

One implementations disclosed here is directed to a LIDAR system. TheLIDAR system includes one or more optical components configured toreceive an optical beam generated by a laser source, wherein the opticalbeam is associated with a local oscillator (LO) signal. In someimplementations, the one or more optical components configured to splitthe optical beam into a first split optical beam and a second splitoptical beam. In some implementations, the one or more opticalcomponents configured to transmit, to an optical device, the first splitoptical beam and the second split optical beam. In some implementations,the one or more optical components configured to receive, from theoptical device, a first reflected beam that is associated with the firstsplit optical beam and a second reflected beam that is associated withthe second split optical beam. In some implementations, the one or moreoptical components configured to pair the first reflected beam with theLO signal and the second reflected beam with the LO signal.

In another aspect, the present disclosure is directed to a method ofcombining multiple functions of a light detection and ranging (LIDAR)system. In some implementations, the method includes receiving anoptical beam generated by a laser source, wherein the optical beam isassociated with a local oscillator (LO) signal. In some implementations,the method includes splitting the optical beam into a first splitoptical beam and a second split optical beam. In some implementations,the method includes transmitting, to an optical device, the first splitoptical beam and the second split optical beam. In some implementations,the method includes receiving, from the optical device, a firstreflected beam that is associated with the first split optical beam anda second reflected beam that is associated with the second split opticalbeam. In some implementations, the method includes pairing the firstreflected beam with the LO signal and the second reflected beam with theLO signal.

Still other aspects, features, and advantages are readily apparent fromthe following detailed description, simply by illustrating a number ofparticular implementations, including the best mode contemplated forcarrying out the invention. Other implementations are also capable ofother and different features and advantages, and their several detailscan be modified in various obvious respects, all without departing fromthe spirit and scope of the invention. Accordingly, the drawings anddescription are to be regarded as illustrative in nature, and not asrestrictive.

BRIEF DESCRIPTION OF THE FIGURES

Implementations are illustrated by way of example, and not by way oflimitation, in the figures of the accompanying drawings in which likereference numerals refer to similar elements and in which:

FIG. 1A is a block diagram illustrating an example of a systemenvironment for autonomous vehicles according to some implementations;

FIG. 1B is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations;

FIG. 1C is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations;

FIG. 1D is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations;

FIG. 2 is a block diagram illustrating an example environment of a LIDARsystem for autonomous vehicles, according to some implementations;

FIG. 3 is a block diagram depicting an example coherent LIDARtransceiver for operating of a vehicle, according to someimplementations;

FIG. 4 is a block diagram depicting an example coherent LIDARtransceiver on two semiconductor substrates, according to someimplementations; and

FIG. 5 is a flow chart that illustrates an example method for combiningmultiple functions of a LIDAR system, according to an implementation.

DETAILED DESCRIPTION

A LIDAR system may include a transmit (Tx) path and a receive (Rx) path.The transmit (Tx) path may include a laser source for providing a lightsignal (sometimes referred to as, “beam”) that is derived from (orassociated with) a local oscillator (LO) signal, one or more modulatorsfor modulating a phase and/or a frequency of the light signal usingContinuous Wave (CW) modulation or quasi-CW modulation, and an amplifierfor amplifying the modulated signal before sending the signal to optics(e.g., an oscillatory scanner, a unidirectional scanner, a Risley prism,a circulator optic, and/or a beam collimator, etc.).

The optics are configured to steer the amplified signal that it receivesfrom the Tx path into an environment within a given field of view towardan object, receive a returned signal reflected back from the object, andprovide the returned signal to the receive (RX) path.

The receive (Rx) path may include a mixer (e.g., 50/50) for mixing theLO signal with the returned signal to generate a down-converted signal,and a transimpedance (TIA) amplifier for amplifying the down-convertedsignal. The RX path provides the down-converted signal (now amplified)to an autonomous vehicle control system for determining a distance tothe object and/or measuring the velocity of the object.

In conventional LIDAR systems, fiber coupling (sometimes referred to as,“fiber cable”) is used to interconnect the Tx path, the Rx path, and theoptics. The fiber coupling provides flexibility during testing anddevelopment of the LIDAR system in that it allows different channels tobe used with different Tx/Rx apertures and optical circulation methods.

However, the bulkiness of fiber coupling limits the capability for aLIDAR designer to add additional channels—each requiring even more fibercoupling—and/or to scale the LIDAR system down to the dimensionsrequired for efficient, automotive applications.

Accordingly, the present disclosure is directed to systems and methodsfor combining multiple functions (e.g., splitting, collecting,combining, redirecting, pairing, etc.) of a LIDAR system, to support theoperation of a vehicle.

In general, as described in the below passages, a Tx path of amulti-channel coherent LIDAR transceiver may receive (via Tx inputs) anoptical beam from a laser source. The laser source may generate theoptical beam based on an LO signal. The Tx path of the coherent LIDARtransceiver may split (e.g., multiply, duplicate, reproduce, etc.) theoptical beam into multiple paths and provide emission of the opticalbeams into free space (via Tx outputs) toward one or more objects. An Rxpath of the multi-channel coherent LIDAR transceiver may receive (via Rxinputs) the returned light that is reflected back from the one or moreobjects into Rx waveguides. Each of the Rx waveguides may be paired witha respective Tx output of the Tx path. The Rx path may split the LOsignal into multiple LO signals, which are then combined with thereturned light from the Rx waveguides using splitters (e.g., 50/50). TheRx path may provide (via Rx outputs) the combined signals to one or moredetectors.

Various example implementations described herein may include one or moreof the following features: (1) the Tx and LO inputs of the coherentLIDAR transceiver may be divided into two inputs each, which may improvematching with a LIDAR engine architecture; (2) the Tx/Rx outputs to freespace may occur along one edge of the coherent LIDAR transceiver withwaveguides interleaving the Tx/Rx outputs (e.g., Tx-Rx-Tx-Rx, etc.),where the pitch is defined by the requirements of the free spacecirculation and/or beam collimation optics; (3) the LO and Tx inputs maybe paired (e.g., LO_A, LO_B; Tx_A, Tx_B, etc.) to function asindependent subsystems; (4) the input power levels to the Tx inputs maybe large (e.g., >1 Watt each); (5) the fiber to the coherent LIDARtransceiver input coupling may accept high power; (6) the scattering ofthe Tx paths (sometimes referred to as, “directivity”) into the Rx paths(e.g., toward the detector) may be very small while being interleaved;(7) reflections from the output faces maybe minimized (e.g., an Angledpolish of the coherent LIDAR transceiver may be used); (8) as the outputbeam quality may be defined by the output of the waveguide, the outputmode of the coherent LIDAR transceiver must have high quality (e.g., alow distortion from a transverse electromagnetic (TEM00) beam); (9) thefunctions (e.g., splitting, collecting, combining, redirecting, pairing,etc.) of a LIDAR system may be combined into one integrated photonicdevice; and (10) the coherent LIDAR transceiver may be implemented usinga programmable logic controller (PLC).

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present disclosure. It will be apparent, however,to one skilled in the art that the present disclosure may be practicedwithout these specific details. In other instances, well-knownstructures and devices are shown in block diagram form in order to avoidunnecessarily obscuring the present disclosure.

1. System Environment for Autonomous Vehicles

FIG. 1A is a block diagram illustrating an example of a systemenvironment for autonomous vehicles according to some implementations.

Referring to FIG. 1A, an example autonomous vehicle 100 within which thevarious techniques disclosed herein may be implemented. The vehicle 100,for example, may include a powertrain 102 including a prime mover 104powered by an energy source 106 and capable of providing power to adrivetrain 108, as well as a control system 110 including a directioncontrol 112, a powertrain control 114, and a brake control 116. Thevehicle 100 may be implemented as any number of different types ofvehicles, including vehicles capable of transporting people and/orcargo, and capable of traveling in various environments, and it will beappreciated that the aforementioned components 102-116 can vary widelybased upon the type of vehicle within which these components areutilized.

For simplicity, the implementations discussed hereinafter will focus ona wheeled land vehicle such as a car, van, truck, bus, etc. In suchimplementations, the prime mover 104 may include one or more electricmotors and/or an internal combustion engine (among others). The energysource may include, for example, a fuel system (e.g., providinggasoline, diesel, hydrogen, etc.), a battery system, solar panels orother renewable energy source, and/or a fuel cell system. The drivetrain108 can include wheels and/or tires along with a transmission and/or anyother mechanical drive components to convert the output of the primemover 104 into vehicular motion, as well as one or more brakesconfigured to controllably stop or slow the vehicle 100 and direction orsteering components suitable for controlling the trajectory of thevehicle 100 (e.g., a rack and pinion steering linkage enabling one ormore wheels of the vehicle 100 to pivot about a generally vertical axisto vary an angle of the rotational planes of the wheels relative to thelongitudinal axis of the vehicle). In some implementations, combinationsof powertrains and energy sources may be used (e.g., in the case ofelectric/gas hybrid vehicles), and in some instances multiple electricmotors (e.g., dedicated to individual wheels or axles) may be used as aprime mover.

The direction control 112 may include one or more actuators and/orsensors for controlling and receiving feedback from the direction orsteering components to enable the vehicle 100 to follow a desiredtrajectory. The powertrain control 114 may be configured to control theoutput of the powertrain 102, e.g., to control the output power of theprime mover 104, to control a gear of a transmission in the drivetrain108, etc., thereby controlling a speed and/or direction of the vehicle100. The brake control 116 may be configured to control one or morebrakes that slow or stop vehicle 100, e.g., disk or drum brakes coupledto the wheels of the vehicle.

Other vehicle types, including but not limited to off-road vehicles,all-terrain or tracked vehicles, construction equipment etc., willnecessarily utilize different powertrains, drivetrains, energy sources,direction controls, powertrain controls and brake controls. Moreover, insome implementations, some of the components can be combined, e.g.,where directional control of a vehicle is primarily handled by varyingan output of one or more prime movers. Therefore, implementationsdisclosed herein are not limited to the particular application of theherein-described techniques in an autonomous wheeled land vehicle.

Various levels of autonomous control over the vehicle 100 can beimplemented in a vehicle control system 120, which may include one ormore processors 122 and one or more memories 124, with each processor122 configured to execute program code instructions 126 stored in amemory 124. The processors(s) can include, for example, graphicsprocessing unit(s) (“GPU(s)”)) and/or central processing unit(s)(“CPU(s)”).

Sensors 130 may include various sensors suitable for collectinginformation from a vehicle's surrounding environment for use incontrolling the operation of the vehicle. For example, sensors 130 caninclude radar sensor 134, LIDAR (Light Detection and Ranging) sensor136, a 3D positioning sensors 138, e.g., any of an accelerometer, agyroscope, a magnetometer, or a satellite navigation system such as GPS(Global Positioning System), GLONASS (Globalnaya NavigazionnayaSputnikovaya Sistema, or Global Navigation Satellite System), BeiDouNavigation Satellite System (BDS), Galileo, Compass, etc. The 3Dpositioning sensors 138 can be used to determine the location of thevehicle on the Earth using satellite signals. The sensors 130 caninclude a camera 140 and/or an IMU (inertial measurement unit) 142. Thecamera 140 can be a monographic or stereographic camera and can recordstill and/or video images. The IMU 142 can include multiple gyroscopesand accelerometers capable of detecting linear and rotational motion ofthe vehicle in three directions. One or more encoders (not illustrated),such as wheel encoders may be used to monitor the rotation of one ormore wheels of vehicle 100. Each sensor 130 can output sensor data atvarious data rates, which may be different than the data rates of othersensors 130.

The outputs of sensors 130 may be provided to a set of controlsubsystems 150, including, a localization subsystem 152, a planningsubsystem 156, a perception subsystem 154, and a control subsystem 158.The localization subsystem 152 can perform functions such as preciselydetermining the location and orientation (also sometimes referred to as“pose”) of the vehicle 100 within its surrounding environment, andgenerally within some frame of reference. The location of an autonomousvehicle can be compared with the location of an additional vehicle inthe same environment as part of generating labeled autonomous vehicledata. The perception subsystem 154 can perform functions such asdetecting, tracking, determining, and/or identifying objects within theenvironment surrounding vehicle 100. A machine learning model inaccordance with some implementations can be utilized in trackingobjects. The planning subsystem 156 can perform functions such asplanning a trajectory for vehicle 100 over some timeframe given adesired destination as well as the static and moving objects within theenvironment. A machine learning model in accordance with someimplementations can be utilized in planning a vehicle trajectory. Thecontrol subsystem 158 can perform functions such as generating suitablecontrol signals for controlling the various controls in the vehiclecontrol system 120 in order to implement the planned trajectory of thevehicle 100. A machine learning model can be utilized to generate one ormore signals to control an autonomous vehicle to implement the plannedtrajectory.

It will be appreciated that the collection of components illustrated inFIG. 1A for the vehicle control system 120 is merely exemplary innature. Individual sensors may be omitted in some implementations.Additionally or alternatively, in some implementations, multiple sensorsof types illustrated in FIG. 1A may be used for redundancy and/or tocover different regions around a vehicle, and other types of sensors maybe used. Likewise, different types and/or combinations of controlsubsystems may be used in other implementations. Further, whilesubsystems 152-158 are illustrated as being separate from processor 122and memory 124, it will be appreciated that in some implementations,some or all of the functionality of a subsystem 152-158 may beimplemented with program code instructions 126 resident in one or morememories 124 and executed by one or more processors 122, and that thesesubsystems 152-158 may in some instances be implemented using the sameprocessor(s) and/or memory. Subsystems may be implemented at least inpart using various dedicated circuit logic, various processors, variousfield programmable gate arrays (“FPGA”), various application-specificintegrated circuits (“ASIC”), various real time controllers, and thelike, as noted above, multiple subsystems may utilize circuitry,processors, sensors, and/or other components. Further, the variouscomponents in the vehicle control system 120 may be networked in variousmanners.

In some implementations, the vehicle 100 may also include a secondaryvehicle control system (not illustrated), which may be used as aredundant or backup control system for the vehicle 100. In someimplementations, the secondary vehicle control system may be capable offully operating the autonomous vehicle 100 in the event of an adverseevent in the vehicle control system 120, while in other implementations,the secondary vehicle control system may only have limitedfunctionality, e.g., to perform a controlled stop of the vehicle 100 inresponse to an adverse event detected in the primary vehicle controlsystem 120. In still other implementations, the secondary vehiclecontrol system may be omitted.

In general, an innumerable number of different architectures, includingvarious combinations of software, hardware, circuit logic, sensors,networks, etc. may be used to implement the various componentsillustrated in FIG. 1A. Each processor may be implemented, for example,as a microprocessor and each memory may represent the random accessmemory (“RAM”) devices comprising a main storage, as well as anysupplemental levels of memory, e.g., cache memories, non-volatile orbackup memories (e.g., programmable or flash memories), read-onlymemories, etc. In addition, each memory may be considered to includememory storage physically located elsewhere in the vehicle 100, e.g.,any cache memory in a processor, as well as any storage capacity used asa virtual memory, e.g., as stored on a mass storage device or anothercomputer controller. One or more processors illustrated in FIG. 1A, orentirely separate processors, may be used to implement additionalfunctionality in the vehicle 100 outside of the purposes of autonomouscontrol, e.g., to control entertainment systems, to operate doors,lights, convenience features, etc.

In addition, for additional storage, the vehicle 100 may include one ormore mass storage devices, e.g., a removable disk drive, a hard diskdrive, a direct access storage device (“DASD”), an optical drive (e.g.,a CD drive, a DVD drive, etc.), a solid state storage drive (“SSD”),network attached storage, a storage area network, and/or a tape drive,among others.

Furthermore, the vehicle 100 may include a user interface 164 to enablevehicle 100 to receive a number of inputs from and generate outputs fora user or operator, e.g., one or more displays, touchscreens, voiceand/or gesture interfaces, buttons and other tactile controls, etc.Otherwise, user input may be received via another computer or electronicdevice, e.g., via an app on a mobile device or via a web interface.

Moreover, the vehicle 100 may include one or more network interfaces,e.g., network interface 162, suitable for communicating with one or morenetworks 170 (e.g., a Local Area Network (“LAN”), a wide area network(“WAN”), a wireless network, and/or the Internet, among others) topermit the communication of information with other computers andelectronic device, including, for example, a central service, such as acloud service, from which the vehicle 100 receives environmental andother data for use in autonomous control thereof. Data collected by theone or more sensors 130 can be uploaded to a computing system 172 viathe network 170 for additional processing. In some implementations, atime stamp can be added to each instance of vehicle data prior touploading.

Each processor illustrated in FIG. 1A, as well as various additionalcontrollers and subsystems disclosed herein, generally operates underthe control of an operating system and executes or otherwise relies uponvarious computer software applications, components, programs, objects,modules, data structures, etc., as will be described in greater detailbelow. Moreover, various applications, components, programs, objects,modules, etc. may also execute on one or more processors in anothercomputer coupled to vehicle 100 via network 170, e.g., in a distributed,cloud-based, or client-server computing environment, whereby theprocessing required to implement the functions of a computer program maybe allocated to multiple computers and/or services over a network.

In general, the routines executed to implement the variousimplementations described herein, whether implemented as part of anoperating system or a specific application, component, program, object,module or sequence of instructions, or even a subset thereof, will bereferred to herein as “program code”. Program code can include one ormore instructions that are resident at various times in various memoryand storage devices, and that, when read and executed by one or moreprocessors, perform the steps necessary to execute steps or elementsembodying the various aspects of the present disclosure. Moreover, whileimplementations have and hereinafter will be described in the context offully functioning computers and systems, it will be appreciated that thevarious implementations described herein are capable of beingdistributed as a program product in a variety of forms, and thatimplementations can be implemented regardless of the particular type ofcomputer readable media used to actually carry out the distribution.

Examples of computer readable media include tangible, non-transitorymedia such as volatile and non-volatile memory devices, floppy and otherremovable disks, solid state drives, hard disk drives, magnetic tape,and optical disks (e.g., CD-ROMs, DVDs, etc.) among others.

In addition, various program code described hereinafter may beidentified based upon the application within which it is implemented ina specific implementation. However, it should be appreciated that anyparticular program nomenclature that follows is used merely forconvenience, and thus the present disclosure should not be limited touse solely in any specific application identified and/or implied by suchnomenclature. Furthermore, given the typically endless number of mannersin which computer programs may be organized into routines, procedures,methods, modules, objects, and the like, as well as the various mannersin which program functionality may be allocated among various softwarelayers that are resident within a typical computer (e.g., operatingsystems, libraries, API's, applications, applets, etc.), it should beappreciated that the present disclosure is not limited to the specificorganization and allocation of program functionality described herein.

The environment illustrated in FIG. 1A is not intended to limitimplementations disclosed herein. Indeed, other alternative hardwareand/or software environments may be used without departing from thescope of implementations disclosed herein.

2. FM LIDAR for Automotive Applications

A truck can include a LIDAR system (e.g., vehicle control system 120 inFIG. 1A, LIDAR system 201 in FIG. 2 , etc.). In some implementations,the LIDAR system can use frequency modulation to encode an opticalsignal and scatter the encoded optical signal into free-space usingoptics. By detecting the frequency differences between the encodedoptical signal and a returned signal reflected back from an object, thefrequency modulated (FM) LIDAR system can determine the location of theobject and/or precisely measure the velocity of the object using theDoppler effect. In some implementations, an FM LIDAR system may use acontinuous wave (referred to as, “FMCW LIDAR”) or a quasi-continuouswave (referred to as, “FMQW LIDAR”). In some implementations, the LIDARsystem can use phase modulation (PM) to encode an optical signal andscatters the encoded optical signal into free-space using optics.

An FM or phase-modulated (PM) LIDAR system may provide substantialadvantages over conventional LIDAR systems with respect to automotiveand/or commercial trucking applications. To begin, in some instances, anobject (e.g., a pedestrian wearing dark clothing) may have a lowreflectivity, in that it only reflects back to the sensors (e.g.,sensors 130 in FIG. 1A) of the FM or PM LIDAR system a low amount (e.g.,10% or less) of the light that hit the object. In other instances, anobject (e.g., a road sign) may have a high reflectivity (e.g., above10%), in that it reflects back to the sensors of the FM LIDAR system ahigh amount of the light that hit the object.

Regardless of the object's reflectivity, an FM LIDAR system may be ableto detect (e.g., classify, recognize, discover, etc.) the object atgreater distances (e.g., 2×) than a conventional LIDAR system. Forexample, an FM LIDAR system may detect a low reflectivity object beyond300 meters, and a high reflectivity object beyond 400 meters.

To achieve such improvements in detection capability, the FM LIDARsystem may use sensors (e.g., sensors 130 in FIG. 1A). In someimplementations, these sensors can be single photon sensitive, meaningthat they can detect the smallest amount of light possible. While an FMLIDAR system may, in some applications, use infrared wavelengths (e.g.,950 nm, 1550 nm, etc.), it is not limited to the infrared wavelengthrange (e.g., near infrared: 800 nm-1500 nm; middle infrared: 1500nm-5600 nm; and far infrared: 5600 nm-1,000,000 nm). By operating the FMor PM LIDAR system in infrared wavelengths, the FM or PM LIDAR systemcan broadcast stronger light pulses or light beams while meeting eyesafety standards. Conventional LIDAR systems are often not single photonsensitive and/or only operate in near infrared wavelengths, requiringthem to limit their light output (and distance detection capability) foreye safety reasons.

Thus, by detecting an object at greater distances, an FM LIDAR systemmay have more time to react to unexpected obstacles. Indeed, even a fewmilliseconds of extra time could improve safety and comfort, especiallywith heavy vehicles (e.g., commercial trucking vehicles) that aredriving at highway speeds.

Another advantage of an FM LIDAR system is that it provides accuratevelocity for each data point instantaneously. In some implementations, avelocity measurement is accomplished using the Doppler effect whichshifts frequency of the light received from the object based at leastone of the velocity in the radial direction (e.g., the direction vectorbetween the object detected and the sensor) or the frequency of thelaser signal. For example, for velocities encountered in on-roadsituations where the velocity is less than 100 meters per second (m/s),this shift at a wavelength of 1550 nanometers (nm) amounts to thefrequency shift that is less than 130 megahertz (MHz). This frequencyshift is small such that it is difficult to detect directly in theoptical domain. However, by using coherent detection in FMCW, PMCW, orFMQW LIDAR systems, the signal can be converted to the RF domain suchthat the frequency shift can be calculated using various signalprocessing techniques. This enables the autonomous vehicle controlsystem to process incoming data faster.

Instantaneous velocity calculation also makes it easier for the FM LIDARsystem to determine distant or sparse data points as objects and/ortrack how those objects are moving over time. For example, an FM LIDARsensor (e.g., sensors 130 in FIG. 1A) may only receive a few returns(e.g., hits) on an object that is 300 m away, but if those return give avelocity value of interest (e.g., moving towards the vehicle at >70mph), then the FM LIDAR system and/or the autonomous vehicle controlsystem may determine respective weights to probabilities associated withthe objects.

Faster identification and/or tracking of the FM LIDAR system gives anautonomous vehicle control system more time to maneuver a vehicle. Abetter understanding of how fast objects are moving also allows theautonomous vehicle control system to plan a better reaction.

Another advantage of an FM LIDAR system is that it has less staticcompared to conventional LIDAR systems. That is, the conventional LIDARsystems that are designed to be more light-sensitive typically performpoorly in bright sunlight. These systems also tend to suffer fromcrosstalk (e.g., when sensors get confused by each other's light pulsesor light beams) and from self-interference (e.g., when a sensor getsconfused by its own previous light pulse or light beam). To overcomethese disadvantages, vehicles using the conventional LIDAR systems oftenneed extra hardware, complex software, and/or more computational powerto manage this “noise.”

In contrast, FM LIDAR systems do not suffer from these types of issuesbecause each sensor is specially designed to respond only to its ownlight characteristics (e.g., light beams, light waves, light pulses). Ifthe returning light does not match the timing, frequency, and/orwavelength of what was originally transmitted, then the FM sensor canfilter (e.g., remove, ignore, etc.) out that data point. As such, FMLIDAR systems produce (e.g., generates, derives, etc.) more accuratedata with less hardware or software requirements, enabling safer andsmoother driving.

Lastly, an FM LIDAR system is easier to scale than conventional LIDARsystems. As more self-driving vehicles (e.g., cars, commercial trucks,etc.) show up on the road, those powered by an FM LIDAR system likelywill not have to contend with interference issues from sensor crosstalk.Furthermore, an FM LIDAR system uses less optical peak power thanconventional LIDAR sensors. As such, some or all of the opticalcomponents for an FM LIDAR can be produced on a single chip, whichproduces its own benefits, as discussed herein.

2.1 Commercial Trucking

FIG. 1B is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations. The environment 100B includes a commercial truck102B for hauling cargo 106B. In some implementations, the commercialtruck 102B may include vehicles configured to long-haul freighttransport, regional freight transport, intermodal freight transport(i.e., in which a road-based vehicle is used as one of multiple modes oftransportation to move freight), and/or any other road-based freighttransport applications. In some implementations, the commercial truck102B may be a flatbed truck, a refrigerated truck (e.g., a reefertruck), a vented van (e.g., dry van), a moving truck, etc. In someimplementations, the cargo 106B may be goods and/or produce. In someimplementations, the commercial truck 102B may include a trailer tocarry the cargo 106B, such as a flatbed trailer, a lowboy trailer, astep deck trailer, an extendable flatbed trailer, a sidekit trailer,etc.

The environment 100B includes an object 110B (shown in FIG. 1B asanother vehicle) that is within a distance range that is equal to orless than 30 meters from the truck.

The commercial truck 102B may include a LIDAR system 104B (e.g., an FMLIDAR system, vehicle control system 120 in FIG. 1A, LIDAR system 201 inFIG. 2 , etc.) for determining a distance to the object 110B and/ormeasuring the velocity of the object 110B. Although FIG. 1B shows thatone LIDAR system 104B is mounted on the front of the commercial truck102B, the number of LIAR system and the mounting area of the LIAR systemon the commercial truck are not limited to a particular number or aparticular area. The commercial truck 102B may include any number ofLIDAR systems 104B (or components thereof, such as sensors, modulators,coherent signal generators, etc.) that are mounted onto any area (e.g.,front, back, side, top, bottom, underneath, and/or bottom) of thecommercial truck 102B to facilitate the detection of an object in anyfree-space relative to the commercial truck 102B.

As shown, the LIDAR system 104B in environment 100B may be configured todetect an object (e.g., another vehicle, a bicycle, a tree, streetsigns, potholes, etc.) at short distances (e.g., 30 meters or less) fromthe commercial truck 102B.

FIG. 1C is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations. The environment 100C includes the same components(e.g., commercial truck 102B, cargo 106B, LIDAR system 104B, etc.) thatare included in environment 100B.

The environment 100C includes an object 110C (shown in FIG. 1C asanother vehicle) that is within a distance range that is (i) more than30 meters and (ii) equal to or less than 150 meters from the commercialtruck 102B. As shown, the LIDAR system 104B in environment 100C may beconfigured to detect an object (e.g., another vehicle, a bicycle, atree, street signs, potholes, etc.) at a distance (e.g., 100 meters)from the commercial truck 102B.

FIG. 1D is a block diagram illustrating an example of a systemenvironment for autonomous commercial trucking vehicles, according tosome implementations. The environment 100D includes the same components(e.g., commercial truck 102B, cargo 106B, LIDAR system 104B, etc.) thatare included in environment 100B.

The environment 100D includes an object 110D (shown in FIG. 1D asanother vehicle) that is within a distance range that is more than 150meters from the commercial truck 102B. As shown, the LIDAR system 104Bin environment 100D may be configured to detect an object (e.g., anothervehicle, a bicycle, a tree, street signs, potholes, etc.) at a distance(e.g., 300 meters) from the commercial truck 102B.

In commercial trucking applications, it is important to effectivelydetect objects at all ranges due to the increased weight and,accordingly, longer stopping distance required for such vehicles. FMLIDAR systems (e.g., FMCW and/or FMQW systems) or PM LIDAR systems arewell-suited for commercial trucking applications due to the advantagesdescribed above. As a result, commercial trucks equipped with suchsystems may have an enhanced ability to safely move both people andgoods across short or long distances, improving the safety of not onlythe commercial truck but of the surrounding vehicles as well. In variousimplementations, such FM or PM LIDAR systems can be used insemi-autonomous applications, in which the commercial truck has a driverand some functions of the commercial truck are autonomously operatedusing the FM or PM LIDAR system, or fully autonomous applications, inwhich the commercial truck is operated entirely by the FM or LIDARsystem, alone or in combination with other vehicle systems.

3. Continuous Wave Modulation and Quasi-Continuous Wave Modulation

In a LIDAR system that uses CW modulation, the modulator modulates thelaser light continuously. For example, if a modulation cycle is 10seconds, an input signal is modulated throughout the whole 10 seconds.Instead, in a LIDAR system that uses quasi-CW modulation, the modulatormodulates the laser light to have both an active portion and an inactiveportion. For example, for a 10 second cycle, the modulator modulates thelaser light only for 8 seconds (sometimes referred to as, “the activeportion”), but does not modulate the laser light for 2 seconds(sometimes referred to as, “the inactive portion”). By doing this, theLIDAR system may be able to reduce power consumption for the 2 secondsbecause the modulator does not have to provide a continuous signal.

In Frequency Modulated Continuous Wave (FMCW) LIDAR for automotiveapplications, it may be beneficial to operate the LIDAR system usingquasi-CW modulation where FMCW measurement and signal processingmethodologies are used, but the light signal is not in the on-state(e.g., enabled, powered, transmitting, etc.) all the time. In someimplementations, Quasi-CW modulation can have a duty cycle that is equalto or greater than 1% and up to 50%. If the energy in the off-state(e.g., disabled, powered-down, etc.) can be expended during the actualmeasurement time then there may be a boost to signal-to-noise ratio(SNR) and/or a reduction in signal processing requirements to coherentlyintegrate all the energy in the longer time scale.

4. A Coherent LIDAR Transceiver with Multiple Channels

FIG. 2 is a block diagram illustrating an example environment of a LIDARsystem for autonomous vehicles, according to some implementations. Theenvironment 200 includes a LIDAR system 201 that includes a transmit(Tx) path and a receive (Rx) path. The Tx path includes one or more Txinput/output ports (not shown in FIG. 2 ) and the Rx path includes oneor more Rx input/output ports (not shown in FIG. 2 ).

In some implementations, a semiconductor substrate and/or semiconductorpackage may include the Tx path and the Rx. In some implementations, afirst semiconductor substrate and/or a first semiconductor package mayinclude the Tx path and a second semiconductor substrate and/or a secondsemiconductor package may include the Rx path. In some arrangements, theRx input/output ports and/or the Tx input/output ports may occur alongone or more edges of one or more semiconductor substrates and/orsemiconductor packages.

The environment 200 includes one or more optics 210 (e.g., anoscillatory scanner, a unidirectional scanner, a Risley prism, acirculator optic, and/or a beam collimator, etc.) that are coupled tothe LIDAR system 201. In some implementations, the one or more optics210 may be coupled to the Tx path via the one or more Tx input/outputports. In some implementations, the one or more optics 210 may becoupled to the Rx path via the one or more Rx input/output ports.

The environment 200 includes a vehicle control system 120 (e.g., vehiclecontrol system 120 in FIG. 1 ) that is coupled to the LIDAR system 201.In some implementations, the vehicle control system 120 may be coupledto the Rx path via the one or more Rx input/output ports.

The Tx path includes a laser source 202, a modulator 204A, a modulator204B, and an amplifier 206. The Rx path includes a mixer 208, a detector212, and a transimpedance (TIA) 212. Although FIG. 2 shows only a selectnumber of components and only one input/output channel; the environment200 may include any number of components and/or input/output channels(in any combination) that are interconnected in any arrangement tofacilitate combining multiple functions of a LIDAR system, to supportthe operation of a vehicle.

The laser source 202 is configured to generate a light signal that isderived from (or associated with) a local oscillator (LO) signal. Insome implementations, the light signal may have an operating wavelengththat is equal to or substantially equal to 1550 nanometers. In someimplementations, the light signal may have an operating wavelength thatis between 1400 nanometers and 1600 nanometers.

The laser source 202 is configured to provide the light signal to themodulator 204A, which is configured to modulate a phase and/or afrequency of the light signal based on a first radio frequency (RF)signal (shown in FIG. 2 as, “RF1”) and using Continuous Wave (CW)modulation or quasi-CW modulation to generate a modulated light signal.The modulator 204A is configured to send the modulated light signal tothe amplifier 206. The amplifier 206 is configured to amplify themodulated light signal to generate an amplified light signal to theoptics 210.

The optics 210 are configured to steer the amplified light signal thatit receives from the Tx path into an environment within a given field ofview toward an object 218, receive a returned signal reflected back fromthe object 218, and provide the returned signal to the mixer 208 of theRx path.

The laser source 202 is configured to provide the LO signal to themodulator 204B, which is configured to modulate a phase and/or afrequency of the LO signal based on a second RF signal (shown in FIG. 2as, “RF2”) and using Continuous Wave (CW) modulation or quasi-CWmodulation to generate a modulated LO signal and send the modulated LOsignal to the mixer 208 of the Rx path.

The mixer 208 is configured to mix (e.g., combine, multiply, etc.) themodulated LO signal with the returned signal to generate adown-converted signal and send the down-converted signal to the detector212. In some arrangements, the mixer 208 is configured to send themodulated LO signal to the detector 212.

The detector 212 is configured to generate an electrical signal based onthe down-converted signal and send the electrical signal to the TIA 214.In some arrangements, the detector 212 is configured to generate anelectrical signal based on the down-converted signal and the modulatedsignal.

The TIA 214 is configured to amplify the electrical signal and send theamplified electrical signal to the vehicle control system 120.

In some implementations, the TIA 214 may have a peak noise-equivalentpower (NEP) that is less than 5 picoWatts per square root Hertz (i.e.,5×10⁻¹² Watts per square root Hertz). In some implementations, the TIA214 may have a gain between 4 kiloohms and 25 kiloohms

In some implementations, detector 212 and/or TIA 214 may have a 3decibel bandwidth between 80 kilohertz (kHz) and 650 megahertz (MHz).

The vehicle control system 120 is configured to determine a distance tothe object 218 and/or measures the velocity of the object 218 based onthe one or more electrical signals that it receives from the TIA.

In some implementations, modulator 204A and/or modulator 204B may have abandwidth between 600 megahertz (MHz) and 1000 (MHz).

FIG. 3 is a block diagram depicting an example coherent LIDARtransceiver for operating of a vehicle, according to someimplementations. The environment 300 includes a coherent LIDARtransceiver 301 and detectors 303, 304, 305, 306, 307, 308, 309, 310(collectively referred to as, “detectors 303-310”). A laser source(e.g., laser source 202 in FIG. 2 ) generates an LO signal via a Tx path(e.g., the Tx path in FIG. 2 ) and provides the LO signal (modulated orunmodulated) to an LO input 360 (shown in FIG. 3 as, “LOA-A”). In someimplementations, the LO signal at the LO input 360 is less than 5milliwatts.

The coherent LIDAR transceiver 301 splits the LO signal received at theLO input 360 into LO signal 360-1 and LO signal 360-2. The coherentLIDAR transceiver 301 splits LO signal 360-1 into LO signal 360-1 a andLO signal 360-1 b. The coherent LIDAR transceiver 301 splits LO signal360-2 into LO signal 360-2 a and LO signal 360-2 b.

The laser source provides the LO signal (modulated or unmodulated) to anLO input 366 (shown in FIG. 3 as, “LOA-B”). The coherent LIDARtransceiver 301 splits the LO signal received at the LO input 366 intoLO signal 366-1 and LO signal 366-2. The coherent LIDAR transceiver 301splits LO signal 366-1 into LO signal 366-1 a and LO signal 366-1 b. Thecoherent LIDAR transceiver 301 splits LO signal 366-2 into LO signal366-2 a and LO signal 366-2 b.

The laser source generates a light signal via a Tx path (e.g., the Txpath in FIG. 2 ) and provides the light signal (modulated orunmodulated) to a Tx input 362 (shown in FIG. 3 as, “Tx-A”). Thecoherent LIDAR transceiver 301 splits the light signal received at theTx input 362 into light signal 362-1 and light signal 362-2. Thecoherent LIDAR transceiver 301 splits light signal 362-1 into lightsignal 362-1 a and light signal 362-1 b. The coherent LIDAR transceiver301 splits light signal 362-2 into light signal 362-2 a and light signal362-2 b.

The laser source provides the light signal (modulated or unmodulated) toa Tx input 364 (shown in FIG. 3 as, “Tx-B”). The coherent LIDARtransceiver 301 splits the light signal received at the Tx input 364into light signal 364-1 and light signal 364-2. The coherent LIDARtransceiver 301 splits light signal 364-1 into light signal 364-1 a andlight signal 364-1 b. The coherent LIDAR transceiver 301 splits lightsignal 364-2 into light signal 364-2 a and light signal 364-2 b.

The coherent LIDAR transceiver 301 provides emission of the light signal362-1 a into free space toward one or more objects via Tx output 320,receives the returned light reflected back from an object via Rx input322, and provides the returned light and LO signal 360-2 b to detector303 (shown in FIG. 3 as, “Rx-1”). The detector 303 generates anelectrical signal based on the returned light and/or the LO signal 360-2b.

The coherent LIDAR transceiver 301 provides emission of the light signal362-1 b into free space toward one or more objects via Tx output 324,receives the returned light reflected back from an object via Rx input326, and provides the returned light and LO signal 360-2 a to detector304 (shown in FIG. 3 as, “Rx-2”). The detector 304 generates anelectrical signal based on the returned light and/or the LO signal 360-2a.

The coherent LIDAR transceiver 301 provides emission of the light signal362-2 a into free space toward one or more objects via Tx output 328,receives the returned light reflected back from an object via Rx input330, and provides the returned light and LO signal 360-1 b to detector305 (shown in FIG. 3 as, “Rx-3”). The detector 305 generates anelectrical signal based on the returned light and/or the LO signal 360-1b.

The coherent LIDAR transceiver 301 provides emission of the light signal362-2 b into free space toward one or more objects via Tx output 332,receives the returned light reflected back from an object via Rx input334, and provides the returned light and LO signal 360-1 a to detector306 (shown in FIG. 3 as, “Rx-4”). The detector 306 generates anelectrical signal based on the returned light and/or the LO signal 360-1a.

The coherent LIDAR transceiver 301 provides emission of the light signal364-1 a into free space toward one or more objects via Tx output 336,receives the returned light reflected back from an object via Rx input338, and provides the returned light and LO signal 366-2 b to detector307 (shown in FIG. 3 as, “Rx-5”). The detector 307 generates anelectrical signal based on the returned light and/or the LO signal 366-2b.

The coherent LIDAR transceiver 301 provides emission of the light signal364-1 b into free space toward one or more objects via Tx output 340,receives the returned light reflected back from an object via Rx input342, and provides the returned light and LO signal 366-2 a to detector308 (shown in FIG. 3 as, “Rx-6”). The detector 308 generates anelectrical signal based on the returned light and/or the LO signal 366-2a.

The coherent LIDAR transceiver 301 provides emission of the light signal364-2 a into free space toward one or more objects via Tx output 344,receives the returned light reflected back from an object via Rx input346, and provides the returned light and LO signal 366-1 b to detector309 (shown in FIG. 3 as, “Rx-7”). The detector 309 generates anelectrical signal based on the returned light and/or the LO signal 366-1b.

The coherent LIDAR transceiver 301 provides emission of the light signal364-2 b into free space toward one or more objects via Tx output 348,receives the returned light reflected back from an object via Rx input350, and provides the returned light and LO signal 366-1 a to detector310 (shown in FIG. 3 as, “Rx-8”). The detector 310 generates anelectrical signal based on the returned light and/or the LO signal 366-1a.

In some implementations, a signal crosstalk associated with returnedlight (sometimes referred to as, “reflected beam”) reflected back fromsurfaces internal to the LIDAR sensor and the emission of thecorresponding light signal (e.g., light signal 362-1 a, 362-1 b, 362-2a, 362-2 b, 364-1 a, 364-1 b, 364-2 a, 364-2 b, etc.) is less than orequal to −55 decibels (dB) within 1 megahertz (MHz) and 200 MHz on allother channels relative to the channel for which the reflected beam isobtained.

In some implementations, a scattering of a light signal into itscorresponding returned light that is reflected back from surfacesinternal to the LIDAR sensor is less than or equal to −66 decibels (dB)relative to the transmitted Tx power, where the scattering is associatedwith a polarization that is maintained.

In some implementations, a scattering of a light signal into itscorresponding returned light that is reflected back from surfacesinternal to the LIDAR sensor is equal to or less than −84 decibels (dB)relative to the transmitted Tx power, where the scattering is associatedwith a polarization that is rotated 90 degrees.

In some implementations, a signal crosstalk between any of theelectrical signals that are generated by detectors 303-310 is less thanor equal to −55 decibels (dB) relative to the electrical signalgenerated on another detector within a frequency range of 1 megahertz(MHz) and 200 MHz.

In some implementations, one or more of the detectors 303-310 mayinclude a pair of photodiodes. In some implementations, a pair ofphotodiodes within a detector may have a common mode rejection ratio(CMRR) greater than or equal to 30 decibels (dB).

In some implementations, any of detectors 303-310 may have a 3 decibelbandwidth between 80 kilohertz (kHz) and 650 megahertz (MHz).

In some implementations, one or more detectors 303-310 may have aresponsivity greater than or equal to 0.9 amperes per watt (A/W).

In some implementations, any of the light signals (e.g., light signal362-1 a, 362-1 b, 362-2 a, 362-2 b, 364-1 a, 364-1 b, 364-2 a, 364-2 b,etc.) may have a duty cycle that is equal to or less than 33 percent.

FIG. 4 is a block diagram depicting an example coherent LIDARtransceiver on two semiconductor substrates, according to someimplementations. The environment 400 includes a semiconductor substrate402 that includes the Rx/LO paths and a semiconductor substrate 404 thatincludes the Tx paths. The semiconductor substrates 402 and 404 may beplaced back-to-back with spacing ‘A’ close to the pitch (e.g., thedistance between the centers of two inputs/outputs) in the single chipconcept. In some implementations, the inputs/outputs of a semiconductorsubstrate each have a pitch that is between 31.75 micrometer and 381micrometer.

FIG. 5 is a flow chart that illustrates an example method for combiningmultiple functions of a LIDAR system, according to an implementation.Although steps are depicted in FIG. 5 as integral steps in a particularorder for purposes of illustration, in other implementations, one ormore steps, or portions thereof, are performed in a different order, oroverlapping in time, in series or in parallel, or are omitted, or one ormore additional steps are added, or the method is changed in somecombination of ways. In some implementation, some or all operations ofmethod 500 may be performed by the coherent LIDAR transceiver 301 inFIG. 3 .

The method 500 includes the operation 502 of receiving an optical beamgenerated by a laser source. In some implementations, the optical beamis associated with a local oscillator (LO) signal. The method 500includes the operation 504 of splitting the optical beam into a firstsplit optical beam and a second split optical beam. The method 500includes the operation 506 of transmitting, to an optical device, thefirst split optical beam and the second split optical beam. The method500 includes the operation 508 of receiving, from the optical device, afirst reflected beam that is associated with the first split opticalbeam and a second reflected beam that is associated with the secondsplit optical beam. The method 500 includes the operation 510 of pairingthe first reflected beam with the LO signal and the second reflectedbeam with the LO signal.

The previous description is provided to enable any person skilled in theart to practice the various aspects described herein. Variousmodifications to these aspects will be readily apparent to those skilledin the art, and the generic principles defined herein may be applied toother aspects. Thus, the claims are not intended to be limited to theaspects shown herein, but is to be accorded the full scope consistentwith the language claims, wherein reference to an element in thesingular is not intended to mean “one and only one” unless specificallyso stated, but rather “one or more.” Unless specifically statedotherwise, the term “some” refers to one or more. All structural andfunctional equivalents to the elements of the various aspects describedthroughout the previous description that are known or later come to beknown to those of ordinary skill in the art are expressly incorporatedherein by reference and are intended to be encompassed by the claims.Moreover, nothing disclosed herein is intended to be dedicated to thepublic regardless of whether such disclosure is explicitly recited inthe claims. No claim element is to be construed as a means plus functionunless the element is expressly recited using the phrase “means for.”

It is understood that the specific order or hierarchy of blocks in theprocesses disclosed is an example of illustrative approaches. Based upondesign preferences, it is understood that the specific order orhierarchy of blocks in the processes may be rearranged while remainingwithin the scope of the previous description. The accompanying methodclaims present elements of the various blocks in a sample order, and arenot meant to be limited to the specific order or hierarchy presented.

The previous description of the disclosed implementations is provided toenable any person skilled in the art to make or use the disclosedsubject matter. Various modifications to these implementations will bereadily apparent to those skilled in the art, and the generic principlesdefined herein may be applied to other implementations without departingfrom the spirit or scope of the previous description. Thus, the previousdescription is not intended to be limited to the implementations shownherein but is to be accorded the widest scope consistent with theprinciples and novel features disclosed herein.

The various examples illustrated and described are provided merely asexamples to illustrate various features of the claims. However, featuresshown and described with respect to any given example are notnecessarily limited to the associated example and may be used orcombined with other examples that are shown and described. Further, theclaims are not intended to be limited by any one example.

The foregoing method descriptions and the process flow diagrams areprovided merely as illustrative examples and are not intended to requireor imply that the blocks of various examples must be performed in theorder presented. As will be appreciated by one of skill in the art theorder of blocks in the foregoing examples may be performed in any order.Words such as “thereafter,” “then,” “next,” etc. are not intended tolimit the order of the blocks; these words are simply used to guide thereader through the description of the methods. Further, any reference toclaim elements in the singular, for example, using the articles “a,”“an” or “the” is not to be construed as limiting the element to thesingular.

The various illustrative logical blocks, modules, circuits, andalgorithm blocks described in connection with the examples disclosedherein may be implemented as electronic hardware, computer software, orcombinations of both. To clearly illustrate this interchangeability ofhardware and software, various illustrative components, blocks, modules,circuits, and blocks have been described above generally in terms oftheir functionality. Whether such functionality is implemented ashardware or software depends upon the particular application and designconstraints imposed on the overall system. Skilled artisans mayimplement the described functionality in varying ways for eachparticular application, but such implementation decisions should not beinterpreted as causing a departure from the scope of the presentdisclosure.

The hardware used to implement the various illustrative logics, logicalblocks, modules, and circuits described in connection with the examplesdisclosed herein may be implemented or performed with a general purposeprocessor, a DSP, an ASIC, an FPGA or other programmable logic device,discrete gate or transistor logic, discrete hardware components, or anycombination thereof designed to perform the functions described herein.A general-purpose processor may be a microprocessor, but, in thealternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration. Alternatively, some blocks or methods may be performed bycircuitry that is specific to a given function.

In some exemplary examples, the functions described may be implementedin hardware, software, firmware, or any combination thereof. Ifimplemented in software, the functions may be stored as one or moreinstructions or code on a non-transitory computer-readable storagemedium or non-transitory processor-readable storage medium. The blocksof a method or algorithm disclosed herein may be embodied in aprocessor-executable software module which may reside on anon-transitory computer-readable or processor-readable storage medium.Non-transitory computer-readable or processor-readable storage media maybe any storage media that may be accessed by a computer or a processor.By way of example but not limitation, such non-transitorycomputer-readable or processor-readable storage media may include RAM,ROM, EEPROM, FLASH memory, CD-ROM or other optical disk storage,magnetic disk storage or other magnetic storage devices, or any othermedium that may be used to store desired program code in the form ofinstructions or data structures and that may be accessed by a computer.Disk and disc, as used herein, includes compact disc (CD), laser disc,optical disc, digital versatile disc (DVD), floppy disk, and blu-raydisc where disks usually reproduce data magnetically, while discsreproduce data optically with lasers. Combinations of the above are alsoincluded within the scope of non-transitory computer-readable andprocessor-readable media. Additionally, the operations of a method oralgorithm may reside as one or any combination or set of codes and/orinstructions on a non-transitory processor-readable storage mediumand/or computer-readable storage medium, which may be incorporated intoa computer program product.

The preceding description of the disclosed examples is provided toenable any person skilled in the art to make or use the presentdisclosure. Various modifications to these examples will be readilyapparent to those skilled in the art, and the generic principles definedherein may be applied to some examples without departing from the spiritor scope of the disclosure. Thus, the present disclosure is not intendedto be limited to the examples shown herein but is to be accorded thewidest scope consistent with the following claims and the principles andnovel features disclosed herein.

Notwithstanding that the numerical ranges and parameters setting forththe broad scope are approximations, the numerical values set forth inspecific non-limiting examples are reported as precisely as possible.Any numerical value, however, inherently contains certain errorsnecessarily resulting from the standard deviation found in theirrespective testing measurements at the time of this writing.Furthermore, unless otherwise clear from the context, a numerical valuepresented herein has an implied precision given by the least significantdigit. Thus a value 1.1 implies a value from 1.05 to 1.15. The term“about” is used to indicate a broader range centered on the given value,and unless otherwise clear from the context implies a broader rangearound the least significant digit, such as “about 1.1” implies a rangefrom 1.0 to 1.2. If the least significant digit is unclear, then theterm “about” implies a factor of two, e.g., “about X” implies a value inthe range from 0.5× to 2×, for example, about 100 implies a value in arange from 50 to 200. Moreover, all ranges disclosed herein are to beunderstood to encompass any and all sub-ranges subsumed therein. Forexample, a range of “less than 10” for a positive only parameter caninclude any and all sub-ranges between (and including) the minimum valueof zero and the maximum value of 10, that is, any and all sub-rangeshaving a minimum value of equal to or greater than zero and a maximumvalue of equal to or less than 10 (e.g., 1 to 4).

Some implementations of the present disclosure are described below inthe context of one or more hi-res Doppler LIDAR systems that are mountedonto an area (e.g., front, back, side, top, and/or bottom) of a personalautomobile; but, implementations are not limited to this context. Inother implementations, one or multiple systems of the same type or otherhigh resolution LIDAR, with or without Doppler components, withoverlapping or non-overlapping fields of view or one or more suchsystems mounted on smaller or larger land, sea or air vehicles, pilotedor autonomous, are employed. In other implementations, the scanninghi-res LIDAR is mounted at temporary or permanent fixed positions onland or sea.

1-20. (canceled)
 21. A light detection and ranging (LIDAR) systemcomprising: a light source configured to generate a transmit light beam;a transceiver comprising: a transmit input configured to receive thetransmit light beam; a plurality of transmit outputs coupled to thetransmit input, the plurality of transmit outputs respectivelyconfigured to transmit the transmit light beam into a surroundingenvironment; and a plurality of receive inputs respectively configuredto receive a return light beam from the surrounding environment; and adetector configured to generate an electrical signal based on the returnlight beam and one or more local oscillator signals associated with thetransmit light beam.
 22. The LIDAR system of claim 21, wherein theplurality of transmit outputs and the plurality of receive inputs arepositioned on a first side of the transceiver.
 23. The LIDAR system ofclaim 22, wherein the plurality of transmit outputs and the plurality ofreceive inputs are interleaved on the first side of the transceiver. 24.The LIDAR system of claim 21, wherein transceiver further comprises: afirst substrate including the plurality of transmit outputs; and asecond substrate including the plurality of receive inputs.
 25. TheLIDAR system of claim 24, wherein the first substrate and the secondsubstrate are placed with a spacing that corresponds to a pitch of theplurality of transmit outputs or the plurality of receive inputs. 26.The LIDAR system of claim 21, wherein: the one or more local oscillatorsignals include a first local oscillator signal and a second localoscillator signal; and the transceiver further comprises a first localoscillator input configured to receive the first local oscillator signaland a second local oscillator input configured to receive the secondlocal oscillator signal.
 27. The LIDAR system of claim 26, wherein thedetector includes a first detector configured to receive the first localoscillator signal from the transceiver and a second detector configuredto receive the second local oscillator signal from the transceiver. 28.The LIDAR system of claim 26, wherein the transmit input is positionedbetween the first local oscillator input and the second local oscillatorinput on a first side of the transceiver.
 29. The LIDAR system of claim28, wherein the plurality of transmit outputs and the plurality ofreceive inputs are positioned on a second side of the transceiver thatis different from the first side of the transceiver.
 30. The LIDARsystem of claim 21, wherein the light source includes a laser and thetransmit light beam includes a laser beam.
 31. The LIDAR system of claim21, further comprising: a fiber coupling configured to couple the lightsource to the transceiver, the fiber coupling including a fiber cableconfigured to deliver the transmit light beam to the transmit input ofthe transceiver.
 32. An autonomous vehicle control system comprising: alight detection and ranging (LIDAR) system comprising: a light sourceconfigured to generate a transmit light beam; a transceiver comprising:a transmit input configured to receive the transmit light beam; aplurality of transmit outputs respectively coupled to the transmitinput, the plurality of transmit outputs respectively configured totransmit the transmit light beam into a surrounding environment; and aplurality of receive inputs respectively configured to receive a returnlight beam from the surrounding environment; and a detector configuredto generate an electrical signal based on the return light beam and oneor more local oscillator signals associated with the transmit lightbeam.
 33. The autonomous vehicle control system of claim 32, wherein theplurality of transmit outputs and the plurality of receive inputs arepositioned on a first side of the transceiver.
 34. The autonomousvehicle control system of claim 32, wherein: the one or more localoscillator signals include a first local oscillator signal and a secondlocal oscillator signal; and the transceiver further comprises a firstlocal oscillator input configured to receive the first local oscillatorsignal and a second local oscillator input configured to receive thesecond local oscillator signal.
 35. The autonomous vehicle controlsystem of claim 34, wherein the detector includes a first detectorconfigured to receive the first local oscillator signal from thetransceiver and a second detector configured to receive the second localoscillator signal from the transceiver.
 36. The autonomous vehiclecontrol system of claim 34, wherein the LIDAR system further comprises:a fiber coupling configured to couple the light source to thetransceiver, the fiber coupling including a fiber cable configured todeliver the transmit light beam to the transmit input of thetransceiver.
 37. The autonomous vehicle control system of claim 34,wherein: the transmit input, the first local oscillator input, and thesecond local oscillator input are positioned on a first side of thetransceiver; and the plurality of transmit outputs and the plurality ofreceive inputs are positioned on a second side of the transceiver thatis different from the first side of the transceiver.
 38. The autonomousvehicle control system of claim 37, wherein the plurality of transmitoutputs and the plurality of receive inputs are interleaved on thesecond side of the transceiver.
 39. The autonomous vehicle controlsystem of claim 32, wherein transceiver further comprises: a firstsubstrate including the plurality of transmit outputs; and a secondsubstrate including the plurality of receive inputs.
 40. An autonomousvehicle comprising: a light detection and ranging (LIDAR) systemcomprising: a light source configured to generate a transmit light beam;a transceiver comprising: a transmit input configured to receive thetransmit light beam; a plurality of transmit outputs respectivelycoupled to the transmit input, the plurality of transmit outputsrespectively configured to transmit the transmit light beam into asurrounding environment; and a plurality of receive inputs respectivelyconfigured to receive a return light beam from the surroundingenvironment; and a detector configured to generate an electrical signalbased on the return light beam and one or more local oscillator signalsassociated with the transmit light beam.